Deploy a model
After you create, train, and evaluate a model, you can deploy it. Although it is possible to score a model without deploying it, a model has to be deployed before it can be scored from the Watson Machine Learning APIs. Also, a model can only have a single deployment. For a trial account, a user can have only one deployed model at a time.
When you deploy a model you save it to the model repository that is associated with your Watson Machine Learning service. Then, you can use your deployed model to score data and build an application.
- Deploy a model from a notebook
- Deploy a Spark model from Flow Editor
- Deploy an IBM SPSS Model from Flow Editor
- Deploy a model from the model builder
- Deploy a model from the project
- Set up deployment for a batch or streaming model
- Deploying and scoring a deep learning model
For more information about continuous learning and model evaluation, see Continuous learning and model evaluation